An image processing apparatus is provided which includes: an inputting unit configured to input image data including a first process color and a second process color; and a determining unit configured to determine a density of the second process color for a target pixel in the inputted image data on the basis of a density of the first process color in the target pixel and on a density of the second process color in a peripheral pixel of the target pixel.
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1. An image processing apparatus for performing a trapping process of increasing a density value of a pixel, comprising:
an inputting unit configured to input image data including a target pixel and a peripheral pixel of the target pixel, the target pixel having a density value of a first color component and a density value of a second color component and the peripheral pixel having a density value of the first color component and a density value of the second color component;
a trapping unit configured to increase, on a basis of at least the density value of the first color component and the density value of the second color component of the target pixel and the density value of the first color component and the density value of the second color component of the peripheral pixel, the density value of the second color component of the target pixel; and
a printing unit configured to print the target pixel by using at least the increased density value of the second color component of the target pixel,
wherein the trapping unit is configured to calculate a first trap rate by using the density value of the first color component of the target pixel, a second trap rate by using the density value of the second color component of the target pixel, a third trap rate by using the density value of the first color component of the peripheral pixel, and a fourth trap rate by using the density value of the second color component of the peripheral pixel,
wherein the trapping unit is configured to calculate a final trap rate by using the first trap rate, the second trap rate, the third trap rate, and the fourth trap rate,
wherein the trapping unit is configured to calculate a trap color density value by using the density value of the second color component of the peripheral pixel and the final trap rate, and
wherein the trapping unit is configured to increase the density value of the second color component of the target pixel to the trap color density value.
2. The image processing apparatus according to
3. The image processing apparatus according to
4. The image processing apparatus according to
5. The image processing apparatus according to
6. The image processing apparatus according to
7. The image processing apparatus according to
wherein the first trap rate indicates a degree of a contribution to the density values of the second color component of the target pixel relative to the density value of the first color component of the target pixel,
wherein the second trap rate indicates a degree of a contribution to the density values of the second color component of the target pixel relative to the density value of the second color component of the target pixel
wherein the first trap rate indicates a degree of a contribution to the density values of the second color component of the target pixel relative to the density value of the first color component of the peripheral pixel
wherein the first trap rate indicates a degree of a contribution to the density values of the second color component of the target pixel relative to the density value of the second color component of the peripheral pixel.
8. The image processing apparatus according to
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1. Field of the Invention
The present invention relates to an image processing apparatus, and a method and a storage medium for controlling the same. More specifically, the present invention relates to an image processing technique for correcting misregistration.
2. Description of the Related Art
In color printers as color image forming apparatuses, multiple printing mechanisms configured to print different colors are arranged next to each other, and perform printing by using cyan, magenta, yellow, and black toners. This type of color printer puts images of the four toners on a recording medium one color after another. Thus, misregistration is likely to occur. Usually, misregistration of a printer occurs lengthways or sideways on the recording medium. It is difficult to completely eliminate misregistration because there are various factors that cause misregistration such as errors in the attached positions of lasers, variations in the conveyance speed of the recording medium, and unevenness in rotations of rotary bodies due to their eccentricity. For this reason, image processing called a trapping process is usually performed to correct misregistration.
Trapping is a technique that prevents a white space resulting from misregistration, by slightly expanding any one or both of colors sitting next to each other so that these colors may be printed to partly overlap one another. The method in Japanese Patent Laid-Open No. 2008-141623 is one technique related to the trapping process. In this method, a trap color is created for each target pixel by using peripheral pixels of the target pixel (hereinafter, referred to as the reference regions). The trap color refers to data on a process color to be used in the trapping of a target pixel at which a white space is formed due to misregistration. In other words, the trap color refers to data on a process color to be expanded.
In Japanese Patent Laid-Open No. 2008-141623, it is determined whether or not there is any pixel to be excluded from the reference regions. In this process, any white pixel or any whiteish light pixel (any pixel with a low density) is determined as an unnecessary pixel and excluded from the reference regions. This is because even if misregistration occurs, the resultant white space would not be noticeable and no trapping is therefore performed in a case where the density is low (light). This determination is done by comparing the density of the reference pixel and a given threshold.
However, some images may include many pixels around the threshold, or other some images may be gradation images. In such cases, the ON/OFF of trapping may be switched, thereby possibly causing degradation of the image.
Now, this problem will be described with reference to
A case under the following conditions, for example, will be described. The trap color (i.e. the process color to be expanded) is assumed to be set to cyan (C) of the background part by the user. Moreover, the threshold of the trap color (i.e. cyan) is assumed to be set to 50 by the user as a condition for the ON/OFF of trapping. As shown in
In a case where the pixel P(4, 5) is the target pixel, the reference regions are a pixel P(4, 4), the pixel P(3, 5), a pixel P(5, 5), and the pixel P(4, 6). Since there is no pixel with a density of cyan (C) above the threshold of 50, no trapping process is performed on the target pixel P(4, 5).
Next, in a case where the pixel P(4, 6) is the target pixel, the reference regions are the pixel P(4, 5), the pixel P(3, 6), a pixel P(5, 6), and a pixel P(4, 7). The density of cyan (C) in the pixel P(3, 6) is 51 and is above the threshold of 50. Thus, trapping is ON. By performing a trapping process in this manner, a result as shown in
An image processing apparatus according to the present invention is an image processing apparatus, comprising: an inputting unit configured to input image data including a first process color and a second process color; and a determining unit configured to determine a density of the second process color for a target pixel in the inputted image data on the basis of a density of the first process color in the target pixel and on a density of the second process color in a peripheral pixel of the target pixel. If a second density is higher than a first density, a density of the second process color for the target pixel determined by the determining unit in a case where a density of the first process color in the target pixel is the second density is higher than a density of the second process color for the target pixel determined by the determining unit in a case where a density of the first process color in the target pixel is the first density.
A natural and fine trapping result can be obtained from an image containing a gradation image or an image with varying densities.
Further features of the present invention will become apparent from the following description of exemplary embodiments (with reference to the attached drawings).
Hereinbelow, embodiments of the present invention will be described with reference to the drawings.
<Embodiment 1>
First, the configuration of the image forming apparatus 100 according to this embodiment will be described. As shown in
Next, the function of each component of the image forming apparatus shown in
Meanwhile, there are two ways to perform a trapping process, in one of which a trapping process is performed on an object data basis, and in the other of which a trapping process is performed on a bitmap after rendering. This embodiment will be described based on an example where a trapping process is performed on a bitmap after rendering.
Next, the configurations and functions of the storage unit 103, the CPU 104, and the image outputting unit 105 of the image forming apparatus shown in
Next, an example of the hardware configuration of the image forming apparatus 100 according to this embodiment will be described with reference to
In the scanner unit 200, when an original is fed onto the platen glass 211, a lamp 212 lights up and a moving unit 213 starts moving. With this movement of the moving unit 213, the scanner unit 200 scans the original on the platen glass 211. In this scanning, light reflected from the original is guided to a CCD image sensor (hereinafter, referred to as “CCD”) 218 by mirrors 214, 215, and 216 and through a lens 217, and the image on the original is formed on the imaging surface of the CCD 218. The CCD 218 converts the image formed on its imaging surface into electric signals. These electric signals are processed in a predetermined manner and then inputted into the image processing unit 102.
On the other hand, in the printer unit 300, light such as laser light modulated according to image data inputted from the image processing unit 102 is caused to strike a rotary polygon mirror rotating at a constant angular velocity, to thereby apply the light onto a photosensitive drum 323 as reflected scan light.
The applied laser light forms an electrostatic latent image on the photosensitive drum 323 serving as an image carrier. This electrostatic latent image is visualized into a toner image (developed image) by toners supplied from developing devices 324C, 324M, 324Y, and 324K serving as developer containing units each containing a developer corresponding to one of the multiple color components. Specifically, an image is produced by executing a series of electrophotographic processes including: transferring a toner image formed on the photosensitive drum 323 onto a recording paper sheet serving as a recording medium; and collecting a small amount of the toner failing to be transferred and remaining on the photosensitive drum 323. Here, the developing devices 324C, 324M, 324Y, and 324K respectively containing cyan (C), magenta (M), yellow (Y), and black (K) toners execute the series of electrophotographic processes in turn while the recording paper sheet wound around a transferring part 325 in a predetermined position is rotated four times. By the time the recording paper sheet is rotated four times, a full color toner image with the four color components is transferred on the recording paper sheet.
The recording paper sheet on which the toner image is transferred is delivered by a conveying belt to a pair of fixing rollers (a heat roller and a pressure roller) 326. Then, the fixing rollers 326 heat and press the recording paper sheet to fix the toner image on the recording paper sheet to the recording paper sheet. The recording paper sheet after passing through the pair of fixing rollers 326 is discharged by a pair of sheet discharging rollers 327 to a sheet discharging unit 330.
The sheet discharging unit 330 is formed of a sheet processing apparatus capable of post processes such as sorting and stapling. Meanwhile, in a case where a two-sided recording mode is set, the rotating direction of the pair of sheet discharging rollers 327 is reversed after the recording paper sheet is conveyed to the pair of sheet discharging rollers 327, to thereby guide the recording paper sheet to a conveying path for re-feed 329 through a flapper 328. The recording paper sheet guided to the conveying path for re-feed 329 is fed again between the photosensitive drum 323 and the transferring part 325 at the timings mentioned above, so that a toner image is transferred onto the back surface of the recording paper sheet.
Next, the procedure of a trapping process will be described.
First, in step S301, the CPU 104 determines whether or not a trapping process is set to be executed on image data (bitmap data) inputted to the image processing unit 102. For example, the user performs test printing. In a case where it is determined from the printing result that misregistration is occurring, the user inputs an instruction to an image forming apparatus to perform a trapping process. The image forming apparatus configures trapping settings based on that instruction. The trapping settings include settings for the trap color (i.e. the process color to be expanded to the adjacent pixel), for example. Moreover, settings for the pixels to be used as reference regions may also be configured. Furthermore, settings that indicate the direction of trapping may also be configured. These settings are inputted from a UI unit not shown and are held in the storage unit 103. The trapping process is terminated in a case where the result of the determination in step S301 shows that the trapping settings are OFF. On the other hand, in a case where the trapping settings are ON, the image processing unit 102 obtains the trap color settings including the designated trap color and performs the following operations on each pixel individually.
In step S302, the image processing unit 102 determines whether or not the density of a process color in the target pixel other than the trap color obtained in step S301 is equal to or higher than a threshold. As will be described later, in a case where the density of the process color in the target pixel other than the trap color is lower than the threshold, no trapping process is performed on the target pixel because even if misregistration occurs, the misregistration would be made unnoticeable by the target pixel. The process then proceeds to step S306. The process proceeds to step S303 in a case where the density of the process color in the target pixel other than the trap color is equal to or higher than the threshold.
In step S303, the image processing unit 102 determines whether or not the density of the trap color, obtained in step S301, in any of the reference pixels set as reference regions is equal to or higher than a threshold. In a case where the density of the trap color in any reference pixel is lower than the threshold, no trapping process is performed on the target pixel because even if misregistration occurs, the misregistration would be made unnoticeable by the target pixel. The process then proceeds to step S306. The process proceeds to a trap-rate determining process in step S304 in a case where the density of the trap color in any reference pixel is equal to or higher than the threshold.
Note that this embodiment involves operations of determining a trap rate in a manner described later and correcting the trap color according to the trap rate. Thus, the thresholds in steps S302 and S303 can be set lower than, for example, the threshold used in the foregoing example described with reference to
In step S304, the image processing unit 102 performs the trap-rate determining process for calculating the trap rate from the density values of the target pixel and the reference pixel. Note that there may be multiple reference pixels above the threshold in step S303. In this case, the pixel with the highest density among the pixels above the threshold can be used as the reference pixel used in step S304 (i.e. a pixel described as the reference pixel in the trap-rate determining process to be discussed later). Details of the trap-rate determining process in step S304 will be described later.
In step S305, the image processing unit 102 performs a density correcting process for correcting the target pixel based on the trap color of the reference pixel used in step S304 and the trap rate determined in step S304. In other words, the image processing unit 102 performs a process in which the trap color with a density corresponding to the trap rate is set as the trap color for the target pixel. The value of the target pixel is derived from the following equation.
Density Value of Trap Color for Target Pixel=cpix×Rate, where cpix is the density value of the trap color in the reference pixel, and Rate is the trap rate. In other words, the density value of the trap color for the target pixel is determined based on the density value of the trap color in the reference pixel and the trap rate determined from the density values of the target pixel and the reference pixel.
However, in a case where Rate=0 in step S305, it means that no trapping is performed. In this case, the density value of the trap color in the target pixel is outputted as is without changing it (no trapping is performed).
In step S306, the image processing unit 102 determines whether or not all the pixels in the inputted image are processed. In a case where there is a next pixel, the next pixel is set as the target pixel, and the process proceeds to step S302. The trapping process is terminated in a case where all the pixels are determined to be processed.
Next, before describing specific processing, a case where a trapping process is necessary will be described. To perform a natural trapping process, determination needs to be done comprehensively based on four types of density. Otherwise, a natural trapping result cannot be obtained. The four types of density include: the density of the trap color in the target pixel; the density of a color in the target pixel other than the trap color; the density of the trap color in a reference pixel; and the density of the color in the reference pixel other than the trap color. This will be specifically described with reference to
A trapping process is necessary in a case where the density of the trap color in the target pixel is low, the density of the color in the target pixel other than the trap color is high, the density of the trap color in any reference pixel is high, and the density of the color in the reference pixel other than the trap color is low. As shown in
In this embodiment, to determine the presence of the above condition, trap rates Rate1, Rate2, Rate3, and Rate4 calculated from the densities in the above pixels are used. Rate1 is a trap rate calculated from the density of the trap color in the target pixel. Rate2 is a trap rate calculated from the density of the process color in the target pixel other than the trap color. Rate3 is a trap rate calculated from the density of the trap color in the reference pixel. Rate4 is a trap rate calculated from the density of the process color in the reference pixel other than the trap color.
Moreover, in this embodiment, the density of the trap color is controlled stepwisely according to the densities of the colors in the above pixels (the four types of density). In this way, a natural trapping result can be obtained regardless of the degrees of the densities of the colors in the pixels.
a: C=153, M=26, Y=0, K=0
b: C=102, M=102, Y=0, K=0
c: C=153, M=102, Y=0, K=0
d: C=26, M=153, Y=0, K=0
e: C=26, M=102, Y=0, K=0
f: C=26, M=153, Y=0, K=0
g: C=153, M=26, Y=0, K=0
h: C=102, M=26, Y=0, K=0
i: C=153, M=102, Y=0, K=0
j: C=153, M=153, Y=0, K=0
Moreover, each of pixels 601 to 615 is a pixel in one of the pixel groups.
Next, a flowchart in
rm_cpix denotes the density of the trap color in the target pixel. rm_rpix denotes the density of a process color in the target pixel other than the trap color. cpix denotes the density of the trap color in the reference pixel. rpix denotes the density of the process color in the reference pixel other than the trap color. Thresholds M1, M2, M3, and M4 can be set to any values. In this embodiment, M1, M2, M3, and M4 are 204, 51, 51, and 204, respectively. Slope1, Slope2, Slope3, and Slope4 each denote a range for adjustment of a trap rate and are all 128. The trap rate can be controlled stepwisely within this trap-rate adjustment range. Rate1 denotes a trap rate calculated from the density of the trap color in the target pixel. Rate2 denotes a trap rate calculated from the density of the color in the target pixel other than the trap color. Rate3 denotes a trap rate calculated from the density of the trap color in the reference pixel. Rate4 denotes a trap rate calculated from the density of the color in the reference pixel other than the trap color. Moreover, Rate denotes a final trap rate. Furthermore, the density in each pixel is an 8-bit (0 to 255) value. The threshold values and the bit number are merely examples, and the present invention is not limited to these.
In the following description, the color other than the trap color means one of the process colors other than the trap color. The following operations in step S401 to S418 are executed repeatedly for all the combinations of the trap color and all the process colors other than the trap color.
In step S401, the image processing unit 102 determines whether or not the trap color rm_cpix in the target pixel is equal to or lower than the threshold M1. In a case where the trap color in the target pixel is higher than the threshold M1, the density of the trap color in the target pixel is sufficiently high. In this case, the image processing unit 102 determines that no trapping is necessary because even if misregistration occurs, the misregistration would not be noticeable, and the process proceeds to step S418. In a case where the trap color in the target pixel is equal to or lower than the threshold M1, trapping may be necessary, and thus the process proceeds to step S402.
For example, in a case where the pixel 601 in
In step S402, the image processing unit 102 determines whether or not the trap color rm_cpix in the target pixel is higher than the value obtained by subtracting Slope1 from the threshold M1. In a case where rm_cpix is higher than (M1−Slope1), it means being within the adjustment range, and thus the process proceeds to step S403 to adjust the trap rate. In a case where rm_cpix is equal to or lower than (M1−Slope1), the image processing unit 102 performs no adjustment and the process proceeds to step S404, where the image processing unit 102 assigns 1 to Rate1 and the process proceeds to step S405.
In step S403, the image processing unit 102 calculates Rate1 from the following equation.
Rate1=(M1−rm_cpix)/Slope1
For example, in a case where the pixel 601 in
For example, in a case where the pixel 603 in
Then, in step S405, the image processing unit 102 determines whether or not the color rm_rpix in the target pixel other than the trap color is equal to or higher than the threshold M2. In a case where the color rm_rpix in the target pixel other than the trap color is lower than the threshold M2, the image processing unit 102 determines that no trapping is necessary because even if misregistration occurs, the misregistration would not be noticeable, and the process proceeds to step S418. In a case where the color rm_rpix in the target pixel other than the trap color is equal to or higher than the threshold M2, misregistration would be noticeable, and thus the process proceeds to step S406.
In step S406, the image processing unit 102 determines whether or not the color rm_rpix in the target pixel other than the trap color is lower than the sum of the threshold M2 and Slope2. In a case where rm_rpix is lower than (M2+Slope2), it means being within the adjustment range, and thus the process proceeds to step S407 to adjust the trap rate. In a case where rm_rpix is equal to or higher than (M2+Slope2), the image processing unit 102 performs no adjustment and the process proceeds to step S408, where the image processing unit 102 assigns 1 to Rate2 and the process proceeds to step S409.
In step S407, the image processing unit 102 derives Rate2 from the following equation.
Rate2=(rm_rpix−M2)/Slope2
For example, in a case where the pixel 605 in
For example, in a case where the pixel 603 in
Then, in step S409, the image processing unit 102 determines whether or not the trap color cpix in the reference pixel is equal to or higher than the threshold M3. In a case where the trap color cpix in the reference pixel is lower than the threshold M3, the image processing unit 102 determines that no trapping is necessary because even if misregistration occurs, the misregistration would not be noticeable, and the process proceeds to step S418. In a case where the trap color cpix in the reference pixel is equal to or higher than the threshold M3, misregistration would be noticeable, and thus the process proceeds to step S410.
In step S410, the image processing unit 102 determines whether or not the trap color cpix in the reference pixel is lower than the sum of the threshold M3 and Slope3. In a case where cpix is lower than (M3+Slope3), it means being within the adjustment range, and thus the process proceeds to step S411 to adjust the trap rate. Ina case where cpix is equal to or higher than (M3+Slope3), the image processing unit 102 performs no adjustment and the process proceeds to step S412, where the image processing unit 102 assigns 1 to Rate3 and the process proceeds to step S413.
In step S411, the image processing unit 102 derives Rate3 from the following equation.
Rate3=(cpix−M3)/Slope3
For example, in a case where the pixel 609 in
For example, in a case where the pixel 611 in
Then, in step S413, the image processing unit 102 determines whether or not the color rpix in the reference pixel other than the trap color is equal to or lower than the threshold M4. In a case where the color rpix in the reference pixel other than the trap color is higher than the threshold M4, the image processing unit 102 determines that no trapping is necessary because even if misregistration occurs, the misregistration would not be noticeable, and the process proceeds to step S418. In a case where the color rpix in the reference pixel other than the trap color is equal to or lower than the threshold M4, trapping may be necessary, and thus the process proceeds to step S414.
In step S414, the image processing unit 102 determines whether or not the color rpix in the reference pixel other than the trap color is higher than the value obtained by subtracting Slope4 from the threshold M4. In a case where rpix is higher than (M4−Slope4), it means being within the adjustment range, and thus the process proceeds to step S415 to adjust the trap rate. In a case where rpix is equal to or lower than (M4−Slope4), the image processing unit 102 performs no adjustment and the process proceeds to step S416, where the image processing unit 102 assigns 1 to Rate4 and the process proceeds to step S417.
In step S416, the image processing unit 102 derives Rate4 from the following equation.
Rate4=(M4−rpix)/Slope4
For example, in a case where the pixel 613 in
For example, in a case where the pixel 615 in
In step S418, the image processing unit 102 assigns 0 to the trap rate Rate in a case where the image processing unit 102 determines in any one of steps S401, S405, S409, and S413 that no trapping is necessary.
In step S417, the image processing unit 102 determines the final trap rate Rate from the following equation by using the trap rates Rate1, Rate2, Rate3, and Rate4 of the corresponding types of density.
Rate=(Rate1+Rate2+Rate3+Rate4)/4
For example, in a case where the pixel 601 in
Rate1=(204−102)/128≈0.8
Rate2=(102−51)/128≈0.4
Rate3=(153−51)/128≈0.8
Rate4 is 1 because the color rpix in the reference pixel other than the trap color is 26 which is lower than (M4−Slope4=76)
From the above,
The image processing unit 102 stores the trap rate determined in step S417 or S418 as the trap rate for the combination of the trap color and the process color other than the trap color which is the current processing target. Then, the process proceeds to step S419.
In step S419, the image processing unit 102 determines whether or not the operations in steps S401 to S418 are executed for all the combinations of the trap color and the other process colors. In a case where the operations are executed for all the combinations, the process proceeds to step S420. On the other hand, in a case where the operations are not yet executed for all the combinations, the image processing unit 102 changes the processing-target color other than the trap color to a process color other than the trap color which is not yet processed. The process then proceeds to step S401.
In step S420, the image processing unit 102 obtains the greatest trap rate among the trap rates for the combinations of the trap color and the process colors other than the trap color stored in step S417 and/or step S418. Moreover, the image processing unit 102 determines the obtained trap rate as the final trap rate Rate for the trap color.
Thus, the density of the trap color, or cyan, for the pixel group k is derived in step S305 as follows by using the trap color cpix in the reference pixel and the trap rate Rate thus determined.
cpix×Rate=153×0.75=115
As mentioned above, a trapping process is necessary in a case where the density of the trap color in the target pixel is low, the density of a color in the target pixel other than the trap color is high, the density of the trap color in any reference pixel is high, and the density of the color in the reference pixel other than the trap color is low. The trap rates Rate1, Rate2, Rate3, and Rate4 derived from the densities in the above pixels are derived such that the closer the pixels are to the above conditions, the higher the trap rates become. Hence, by determining the trap rate Rate from the average of the trap rates Rate1, Rate2, Rate3, and Rate4, it is possible to realize natural trapping under any circumstance.
It should be noted that the trap-rate determining process described above is merely an example. In a case where there are multiple colors other than the trap color, the trap rate may be determined by using the color in the reference pixel that has the highest density among the multiple colors. Alternatively, the average value of the trap rates figured out for all the process colors may be determined as the final trap rate, or each of the above operations may be performed by using some other method. What is important is that the trap rate is determined in such a way as to change gradually according to the densities of the process colors in the target pixel and the reference pixel.
Moreover, in the example described above, the trap rate Rate for the combination of the trap color and each other process color is determined from the average of the trap rates for the aforementioned types of density. However, the present invention is not limited to this case. It is possible to determine the trap rate Rate based on the highest value and the lowest value among the four values, weighting, or mixing.
As described above, in this embodiment, the density of the trap color for trapping (the intensity of trapping) is controlled gradually in a stepwise manner or in a continuous manner by providing an adjustment range based on the densities of the colors in the target pixel and the reference pixel. In this way, it is possible to obtain a fine trapping result even from a gradation image or an image with varying densities. For example, in a case where misregistration occurs in gradation on a printed object, a low density area of the gradation may be printed in a light trap color. By doing so, it is possible to solve the density difference which would otherwise occur due to.
Moreover, by deriving the trap rates Rate1 to Rate4 for the four types of density that need to be taken into consideration at the time of performing trapping, it is possible to obtain a fine trapping result regardless of the relation between the target pixel and the reference pixel in terms of density.
In this embodiment, the method of deriving the trap rate within the adjustment range is linear. However, it is needless to say that the present invention is not limited to this case and the method may be any function or non-linear.
Moreover, although the foregoing example is described by taking an instance where the four colors of CMYK are used, the present invention is applicable to other color combinations.
<Embodiment 2>
Next, image processing according to Embodiment 2 will be described.
This embodiment will be described by taking an example where the trap rate is determined by weighting it according to the distance from the target pixel to the reference pixel which is set as the processing target for determining the trap rate.
The image processing unit 102 corrects the trap rate determined in step S904, based on weighting performed according to the distance from the target pixel to the reference pixel (step S905). In a case where the distance from the target pixel to the reference pixel is R, the trap rate is corrected by using the following equation. Here, distance R=4 in a case where the processing-target reference pixel is away from the target pixel by four pixels, for example.
Corrected Trap Rate Rate′=Trap Rate Rate/Distance R
The image processing unit 102 performs a density correcting process (step S906) for correcting the target pixel based on the reference pixel and the trap rate corrected in step S905. The target pixel value is calculated from the following equation.
Density Value of Trap Color for Target Pixel=cpix×Rate′, where cpix is the density value of the trap color in the reference pixel, and Rate′ is the trap rate. However, as in the case of step S305, the density value of the trap color in the target pixel is outputted as is without changing it (no trapping is performed) if Rate′=0.
The image processing unit 102 determines whether or not all the pixels in the inputted image are processed (step S907). In a case where there is a next pixel, the next pixel is set as the target pixel, and the process proceeds to step S902. The trapping process is terminated in a case where all the pixels are determined to be processed.
By determining the trap rate through the weighting based on the distance from the target pixel to the reference pixel as described above, it is possible to prevent increase in density even in a case where the colors are caused to overlap one another by the trapping process under a condition where the trapping range is wide.
<Other Embodiments>
Each foregoing embodiment is described by taking an image forming apparatus as an example. Moreover, the processes in each foregoing embodiment are described as being performed mainly in the image processing unit (image processing apparatus) inside the image forming apparatus as an example. However, the present invention may be applied to an image processing apparatus connected to an apparatus that performs image formation.
Aspects of the present invention can also be realized by a computer of a system or apparatus (or devices such as a CPU or MPU) that reads out and executes a program recorded on a memory device to perform the functions of the above-described embodiment (s), and by a method, the steps of which are performed by a computer of a system or apparatus by, for example, reading out and executing a program recorded on a memory device to perform the functions of the above-described embodiment(s). For this purpose, the program is provided to the computer for example via a network or from a recording medium of various types serving as the memory device (e.g., computer-readable medium).
While the present invention has been described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. The scope of the following claims is to be accorded the broadest interpretation so as to encompass all such modifications and equivalent structures and functions.
This application claims the benefit of Japanese Patent Application No. 2012-275787, filed Dec. 18, 2012, which is hereby incorporated by reference herein in its entirety.
Patent | Priority | Assignee | Title |
10148854, | Aug 20 2014 | Canon Kabushiki Kaisha | Image processing apparatus, image processing method, and storage medium |
Patent | Priority | Assignee | Title |
4794531, | Nov 07 1984 | Hitachi Medical Corporation | Unsharp masking for image enhancement |
7667869, | Mar 19 2004 | Riso Kagaku Corporation | Image processing device, image processing method, and printer driver |
7961354, | Dec 18 2006 | Canon Kabushiki Kaisha | Image-forming apparatus and method for adjusting total amount of toner in trap |
8164794, | Dec 18 2006 | Canon Kabushiki Kaisha | Image-forming apparatus and method for adjusting total amount of toner in trap |
8199359, | Apr 28 2006 | Kyocera Mita Corporation | System and method for reducing visibility of registration errors in an image to be printed using a digital color printer by convolution with a laplacian kernel |
8253981, | Dec 04 2006 | Canon Kabushiki Kaisha | Formation of a color image by using a plurality of color component materials |
8717623, | Aug 06 2010 | HEWLETT-PACKARD DEVELOPMENT COMPANY, L P | Controller chip and image forming apparatus to perform color mis-registration correction and methods thereof |
8958636, | Jul 28 2010 | MARVELL INTERNATIONAL LTD | Configurable color trapping |
20080259366, | |||
20100079524, | |||
20100118322, | |||
20100238468, | |||
20110128556, | |||
20150015918, | |||
JP2008141623, |
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